System to generate an aggregate interest indication with respect to an information item

ABSTRACT

A system is provided to establish a ranking for published data. The system may include ranking and monitoring components. A number of registrations of user interest in an instance of published data may be determined. A ranking for the instance of published data may be generated based on the number of registrations of user interest in the instance of published data. A user of the system may be enabled to activate a monitoring process to monitor activity pertaining to the instance of published data.

RELATED APPLICATION

The present application is a continuation of U.S. patent applicationSer. No. 11/026,942 filed Dec. 30, 2004 and issued as U.S. Pat. No.7,490,056 on Feb. 10, 2009, which in turn claims the benefit under 35U.S.C. § 119(e) of U.S. Provisional Application No. 60/625,435, filedNov. 4, 2004, the entire content of each application being incorporatedherein by reference.

TECHNICAL FIELD

Exemplary embodiments of the present invention relate generally to thetechnical field of data processing and, in one exemplary embodiment, toa system to generate an aggregate interest indication for an informationitem.

BACKGROUND

A number of websites, such as publishing websites (e.g., newspapers,etc.) and commerce websites (e.g., store or marketplace websites), allowusers to add items that may be offered for sale via such websites tolists that are maintained by the relevant website, on behalf of theuser. For example, certain commerce websites (e.g. Amazon.com) allowusers to add items offered for sale via that website to a so-called“wish list”, which is in effect a registry of items that a particularuser may like to acquire. Similarly, certain marketplace websites (e.g.,eBay.com) allow users to add listings to a “watch list”, responsive towhich the commerce websites conveniently present information (e.g., viaa customized web page or by email) to the relevant user.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example and notlimitation in the figures of the accompanying drawings, in which likereferences indicate similar elements and in which:

FIG. 1 is a diagram of an exemplary network-based commerce system, inaccordance with the invention;

FIG. 2 is a block diagram illustrating exemplary multiple marketplaceand payment applications;

FIG. 3 is a high-level entity-relationship diagram, illustrating variousexemplary tables that may be maintained within databases of the system;

FIG. 4 is a flow chart illustrating a method, according to an exemplaryembodiment of the present invention, to rank, search or otherwisegenerate an interest indication or measure, with respect to aninformation item;

FIG. 5 illustrates an exemplary user interface that is utilized topublish a list of “most watched items”;

FIG. 6 is a flow chart illustrating a method, according to an exemplaryembodiment of the present invention, to create a data structure of saleslistings in which users have expressed or registered in interest;

FIG. 7 is a high level flow chart illustrating a method, according toexemplary embodiment of the present invention, for creating a categorytree for the top n most watched items; and

FIG. 8 shows a diagrammatic representation of machine in the exemplaryform of a computer system within which a set of instructions, forcausing the machine to perform any one or more of the methodologiesdiscussed herein, may be executed.

DETAILED DESCRIPTION

A method and system to generate an aggregate interest indication for aninformation item are described. In the following description, forpurposes of explanation, numerous specific details are set forth inorder to provide a thorough understanding of the present invention. Itwill be evident, however, to one skilled in the art that the presentinvention may be practiced without these specific details.

Exemplary Platform Architecture

FIG. 1 is a network diagram depicting a system 10, according to oneexemplary embodiment of the present invention, having a client-serverarchitecture. A commerce platform, in the exemplary form of anetwork-based commerce system or marketplace 12, provides server-sidefunctionality, via a network 14 (e.g., the Internet) to one or moreclients. FIG. 1 illustrates, for example, a web client 16 (e.g., abrowser, such as the Internet Explorer browser developed by MicrosoftCorporation of Redmond, Wash. State), and a programmatic client 18executing on respective client machines 20 and 22.

Turning specifically to the network-based marketplace 12, an ApplicationProgram Interface (API) server 24 and a web server 26 are coupled to,and provide programmatic and web interfaces respectively to, one or moreapplication servers 28. The application servers 28 host one or moremarketplace applications 30 and payment applications 32. The applicationservers 28 are, in turn, shown to be coupled to one or more databasesservers 34 that facilitate access to one or more databases 36.

The marketplace applications 30 provide a number of marketplacefunctions and services to users that access the marketplace 12. Thepayment applications 32 likewise provide a number of payment servicesand functions to users. The payment applications 30 may allow users toquantify for, and accumulate, value (e.g., in a commercial currency,such as the U.S. dollar, or a proprietary currency, such as “points”) inaccounts, and then later to redeem the accumulated value for products(e.g., goods or services) that are made available via the marketplaceapplications 30. While the marketplace and payment applications 30 and32 are shown in FIG. 1 to both form part of the network-basedmarketplace 12, it will be appreciated that, in alternative embodimentsof the present invention, the payment applications 32 may form part of apayment service that is separate and distinct from the marketplace 12.

Further, while the system 10 shown in FIG. 1 employs a client-serverarchitecture, the present invention is of course not limited to such anarchitecture, and could equally well find application in a distributed,or peer-to-peer, architecture system. The various marketplace andpayment applications 30 and 32 could also be implemented as standalonesoftware programs, which do not necessarily have networkingcapabilities.

The web client 16, it will be appreciated, accesses the variousmarketplace and payment applications 30 and 32 via the web interfacesupported by the web server 26. Similarly, the programmatic client 18accesses the various services and functions provided by the marketplaceand payment applications 30 and 32 via the programmatic interfaceprovided by the API server 24. The programmatic client 18 may, forexample, be a seller application (e.g., the TurboLister applicationdeveloped by eBay Inc., of San Jose, Calif.) to enable sellers to authorand manage listings on the marketplace 12 in an off-line manner, and toperform batch-mode communications between the programmatic client 18 andthe network-based marketplace 12.

FIG. 1 also illustrates a third party application 38, executing on athird party server machine 40, as having programmatic access to thenetwork-based marketplace 12 via the programmatic interface provided bythe API server 24. For example, the third party application 38 may,utilizing information retrieved from the network-based marketplace 12,support one or more features or functions on a website hosted by thethird party. The third party website may, for example, provide one ormore promotional, marketplace or payment functions that are supported bythe relevant applications of the network-based marketplace 12.

Exemplary Marketplace Applications

FIG. 2 is a block diagram illustrating multiple marketplace and paymentapplications 30 that, in one exemplary embodiment of the presentinvention, are provided as part of the network-based marketplace 12. Themarketplace 12 may provide a number of listing and price-settingmechanisms whereby a seller may list goods and/or services for sale, abuyer can express interest in or indicate a desire to purchase suchgoods and/or services, and a price can be set for a transactionpertaining to the goods and/or services. To this end, the marketplaceapplications 30 are shown to include one or more auction applications 44which support auction-format listing and price setting mechanisms (e.g.,English, Dutch, Vickrey, Chinese, Double, Reverse auctions etc.). Thevarious auction applications 44 may also provide a number of features insupport of such auction-format listings, such as a reserve price featurewhereby a seller may specify a reserve price in connection with alisting and a proxy-bidding feature whereby a bidder may invokeautomated proxy bidding.

A number of fixed-price applications 46 support fixed-price listingformats (e.g., the traditional classified advertisement-type listing ora catalogue listing) and buyout-type listings. Specifically, buyout-typelistings (e.g., including the Buy-It-Now (BIN) technology developed byeBay Inc., of San Jose, Calif.) may be offered in conjunction with anauction-format listing, and allow a buyer to purchase goods or services,which are also being offered for sale via an auction, for a fixed-pricethat is typically higher than the starting price of the auction.

Store applications 48 allow sellers to group their listings within a“virtual” store, which may be branded and otherwise personalized by andfor the sellers. Such a virtual store may also offer promotions,incentives and features that are specific and personalized to a relevantseller.

Reputation applications 50 allow parties that transact utilizing thenetwork-based marketplace 12 to establish, build and maintainreputations, which may be made available and published to potentialtrading partners. Consider that where, for example, the network-basedmarketplace 12 supports person-to-person trading, users may have nohistory or other reference information whereby the trustworthiness andcredibility of potential trading partners may be assessed. Thereputation applications 50 allow a user, for example through feedbackprovided by other transaction partners, to establish a reputation withinthe network-based marketplace 12 over time. Other potential tradingpartners may then reference such a reputation for the purposes ofassessing credibility and trustworthiness.

Personalization applications 52 allow users of the marketplace 12 topersonalize various aspects of their interactions with the marketplace12. For example a user may, utilizing an appropriate personalizationapplication 52, create a personalized reference page at whichinformation regarding transactions to which the user is (or has been) aparty may be viewed. Further, a personalization application 52 mayenable a user to personalize listings and other aspects of theirinteractions with the marketplace 12 and other parties.

In one embodiment, the network-based marketplace 12 may support a numberof marketplaces that are customized, for example, for specificgeographic regions. A version of the marketplace 12 may be customizedfor the United Kingdom, whereas another version of the marketplace 12may be customized for the United States. Each of these versions mayoperate as an independent marketplace, or may be customized (orinternationalized) presentations of a common underlying marketplace.

Navigation of the network based-marketplace 12 may be facilitated by oneor more navigation applications 56. For example, a search applicationenables key word searches of listings published via the network-basedmarketplace 12. A browse application allows users to browse variouscategory, catalogue, or inventory data structures according to whichlistings may be classified within the marketplace 12. Various othernavigation applications may be provided to supplement the search andbrowsing applications.

In one embodiment, the navigation applications 56 may include one ormore search enhancement applications 80, which operate to provideinformation to users (e.g., via a “homepage” of the network-basedmarketplace 12) regarding activities that are being performed by a usercommunity. For example in one embodiment, the search enhancementapplications 80 may identify lists of top ranked listings, published bythe network-based marketplace 12. One such a list of top ranked listingsmay be a list of listings that are the most “monitored” by a communityof users, the monitoring function being supported by an interest module82 of the applications 80. For example, the interest module 82 mayenable a user to add a particular listing to a “watch list” or“monitored list” that is maintained by the network-based marketplace 12on behalf of the user. The interest module 82 may also enable users toregister interest with respect to a listing in one of a number of otherways, including by adding a particular listing to a “gift registry” or“wish list” that is maintained for the user. The lists may also berestricted or based on other attributes (e.g., category, price,geographic location of seller, etc.).

The search enhancement applications 80 may also include a ranking module84 that operates to generate lists of “top-ranked listings”, bymeasuring (e.g., counting) various metrics pertaining to listingspublished by the network-based marketplace 12. For example, in oneembodiment, the ranking module 84 may count the number of users thathave registered interest, via the interest module 80, in a particularlisting (e.g., the users may have flagged the listing as being ofpotential interest). The ranking module 84 may then generate an interestindication value (e.g., a count) for each of a number of listings, andthen rank the listings according to the interest indication value. Apredetermined number of “top ranked listings” may then be identified bythe ranking module 84. Such “top-ranked listings” may be published bythe trading platform 12.

In order to make listings, available via the network-based marketplace12, as visually informing and attractive as possible, the marketplaceapplications 30 may include one or more imaging applications 58 whichusers may utilize to upload images for inclusion within listings. Animaging application 58 also operates to incorporate images within viewedlistings. The imaging applications 58 may also support one or morepromotional features, such as image galleries that are presented topotential buyers. For example, sellers may pay an additional fee to havean image included within a gallery of images for promoted items.

Listing creation applications 60 allow sellers conveniently to authorlistings pertaining to goods or services that they wish to transact viathe network-based marketplace 12, and listing management applications 62allow sellers to manage such listings. Specifically, where a particularseller has authored and/or published a large number of listings, themanagement of such listings may present a challenge. The listingmanagement applications 62 provide a number of features (e.g.,auto-relisting (automatically re-listing an expired listing), inventorylevel monitors, etc.) to assist the seller in managing such listings.One or more post-listing management applications 64 also assist sellerswith a number of activities that typically occur post-listing. Forexample, upon completion of an auction facilitated by one or moreauction applications 44, a seller may wish to leave feedback regarding aparticular buyer. To this end, a post-listing management application 64may provide an interface to one or more reputation applications 50, soas to allow the seller conveniently to provide feedback regardingmultiple buyers to the reputation applications 50.

Dispute resolution applications 66 provide mechanisms whereby disputesarising between transacting parties may be resolved. For example, thedispute resolution applications 66 may provide guided procedures wherebythe parties are guided through a number of steps in an attempt to settlea dispute. In the event that the dispute cannot be settled via theguided procedures, the dispute may be escalated to a third partymediator or arbitrator.

A number of fraud prevention applications 68 implement various frauddetection and prevention mechanisms to reduce the occurrence of fraudwithin the marketplace 12.

Messaging applications 70 are responsible for the generation anddelivery of messages to users of the network-based marketplace 12, suchmessages for example advising users regarding the status of listings atthe marketplace 12 (e.g., providing “outbid” notices to bidders duringan auction process or to provide promotional and merchandisinginformation to users).

Merchandising applications 72 support various merchandising functionsthat are made available to sellers to enable sellers to increase salesvia the network-based marketplace 12. The merchandising applications 80also operate the various merchandising features that may be invoked bysellers, and may monitor and track the success of merchandisingstrategies employed by sellers.

The network-based marketplace 12 itself, or one or more parties thattransact via the marketplace 12, may operate loyalty programs that aresupported by one or more loyalty/promotions applications 74. Forexample, a buyer may earn loyalty or promotions points for eachtransaction established and/or concluded with a particular seller, andbe offered a reward for which accumulated loyalty points can beredeemed.

Exemplary Data Structures

FIG. 3 is a high-level entity-relationship diagram, illustrating varioustables 90 that may be maintained within the databases 36, and that areutilized by and support the marketplace and payment applications 30 and32. A user table 92 contains a record for each registered user of thenetwork-based marketplace 12, and may include identifier, address andfinancial instrument information pertaining to each such registereduser. A user may, it will be appreciated, operate as a seller, a buyer,or both, within the network-based marketplace 12. In one exemplaryembodiment of the present invention, a buyer may be a user that hasaccumulated value (e.g., commercial or proprietary currency), and isthen able to exchange the accumulated value for items that are offeredfor sale by the network-based marketplace 12.

The tables 90 also include an items table 94 in which are maintaineditem records for goods and services that are available to be, or havebeen, transacted via the marketplace 12. Each item record within theitems table 94 may furthermore be linked to one or more user recordswithin the user table 92, so as to associate a seller and one or moreactual or potential buyers with each item record.

A transaction table 96 contains a record for each transaction (e.g., apurchase transaction) pertaining to items for which records exist withinthe items table 94.

An order table 98 is populated with order records, each order recordbeing associated with an order. Each order, in turn, may be with respectto one or more transactions for which records exist within thetransactions table 96.

Bid records within a bids table 100 each relate to a bid received at thenetwork-based marketplace 12 in connection with an auction-formatlisting supported by an auction application 44. A feedback table 102 isutilized by one or more reputation applications 50, in one exemplaryembodiment, to construct and maintain reputation information concerningusers. A history table 104 maintains a history of transactions to whicha user has been a party. One or more attributes tables 106 recordattribute information pertaining to items for which records exist withinthe items table 94. Considering only a single example of such anattribute, the attributes tables 106 may indicate a currency attributeassociated with a particular item, the currency attribute identifyingthe currency of a price for the relevant item as specified in by aseller.

The tables 90 are further shown to include an association datastructure, in the exemplary form of a watch table 101, that storesassociations between listings, for which records are maintained in theitems table 94, and users, for which records are maintained in the usertable 92. Specifically, the watch table 101 may record registration of auser in a monitoring capacity with respect to one of more listings.

Further, the tables 90 may, in one embodiment, included an interestvalue table 103 in which is stored interest values for each of thelistings for which records are maintained in the items table 94. Aninterest value for each listing may be generated, for example, bycounting the number of unique registrations of user interest (e.g.,monitoring or flagging) in the relevant listing. The interest values asstored within the table 103 may be generated, in one embodiment, by theranking module 84 discussed above with reference to FIG. 2.

According an exemplary embodiment of the present invention, there isprovided a method and system to rank, search or otherwise process,information items that are published via a publication or sales system,based on the degree of user interest with respect to such an informationitem. For example, within the context of a commerce website (e.g., anonline store or electronic marketplace), users of the relevant commercesystem may indicate or register interest with respect to a specificinformation item (e.g., a product or service listing) in a number ofways. A user may add a particular listing to a registry (e.g., a “wishlist”) or to a “watch list”, under which the commerce system may monitoractivity pertaining to the listing with a view to providing automaticnotifications regarding any activity. The commerce website may alsopresent customized information including information regarding listingsthat have been added to the “watch list”.

FIG. 4 is a flow chart illustrating a method 120, according to anexemplary embodiment of the present invention, to rank, search orotherwise generate an interest indication or measure, with respect to aninformation item (e.g., a sale listing) that may be published via apublication and/or sales system, such as a network-based marketplace oran electronic commerce system.

The method 120 assumes that the identity of a user, to which informationis made available by a publication and/or sales system, (e.g., thenetwork-based marketplace 12), is known to the system. To this end, auser may have a logged into a website (e.g., using a username/passwordpair) operated by the publication and/or sales system. Alternatively,the identity of the user may be determined by some other mechanism, suchas a cookie deposit by the publication and/or sales system.

At block 122, user identification of a specific information item isreceived at the publication/sales system from the user, via the network.For example, the user may have conducted a search of information items,and have selected a particular information item as being of interest.This identification may comprise, for example, a user clicking onidentification information pertaining to the information item, and theuser thus navigating to a webpage dedicated primarily to the informationitem of interest. Taking a commerce website as an example, a user mayfor example, have “clicked through” a hypertext link presented in a listof search results, to be presented with a webpage providing a detailedsale listing pertaining to it.

Responsive to the user identification of the information item, amechanism may then be presented to the user whereby the user canindicate or register interest in the item (e.g., tag the item). Forexample, continuing the above example of a sale listing presented on acommerce website, a button may be presented within a listing page that,when selected by a user, adds the relevant sale listing to a “wishlist”, registry or “watch list”. In a similar fashion, theidentification of the item may be a user adding the item to a so-calledwebsite “shopping cart.”

In any event, responsive to user indication, via the presentedmechanism, of interest in the information item, an interest indicationis received, at block 124, at the publication and/or sales system, thisinterest indication being received in conjunction with informationidentifying the user. For example, where a session identifier isutilized to maintain state between a client system and a server system,a session identifier may be included within a URL communicated from theclient to the server system, the session identifier operating toidentify the user. Where a cookie is stored on the client machine,information may be extracted from this cookie, and included in theinformation received at the publication and/or sales system, to therebyidentify the user to the system.

At block 126, the publication and/or sales system creates an interestindication data structure association between the user and theinformation item. For example, the publication and/or sales system maysupplement a record, maintained for the user, with information toidentify that the user has expressed or registered interest within aninformation item. In one embodiment, the publication and/or sales systemmay maintain a relational data base, and a relational association may becreated between the user and the relevant information item.

In an alternative embodiment, as opposed to creating an associationbetween the user and the information item, a count of the number ofusers that have expressed or registered interest in a particularinformation item maybe incremented responsive to the receipt of theinterest indication at block 124. In a further embodiment, such a countmay be incremented in addition to the above described association beingcreated.

At block 128, the publication and/or sales system performs a count ofinterest indications with respect to each of a number of informationitems maintained thereby. As mentioned above, this may, in oneembodiment, involve performing a count of the number of associationsbetween each information item and users. In another embodiment, this maysimply involve a read operation to read a number of counts that havebeen previously registered with respect to each of a number ofinformation items.

At block 130, an interest indication value, derived from the countperformed at block 128, may be stored for each information item. Theseinterest indication values may be stored, in one embodiment, in a cachememory structure to thus improve the response times for queries that maybe run against the stored interest indication values.

In one embodiment, the method 120 may then branch to block 132, wherethe publication and/or sales system proceeds to identify the “topranked” information items, based on the interest indication values. Forexample, the “top 10” information items, ranked according to interestindication values, may be identified at block 132. In furtherembodiments, the identification of the “top ranked” information itemsmay include the application of further criteria. For example, onlyinformation items of a particular status (e.g., active), publishedwithin certain time constraints (e.g., published in the last 24 hours),published within certain product or service categories, or includingcertain description information (e.g. meeting a certain price criteria)may be included within the “top ranked” information items.

At block 134, the publication and/or sales system may publish a list ofthe top ranked information items. For example, this list may bepublished on the “homepage” of a website, thereby to provide other usersof the website with a convenient indication of which information items(e.g., sales listings) of the website are receiving interest from acommunity of users.

FIG. 5 illustrates an exemplary user interface, in the form of a webpage 160, that is utilized to publish a list of “most watched items”162, this list constituting an example of a list of top rankedinformation items that may be published by the publication and/or salessystem.

Returning to the method 120, from block 130, the method 120 may alsobranch to block 136, where the publication and/or sales system receivesa search request, including interest indication criteria as well asfurther criteria. For example, the search request may be received from auser, and may specify that only information items having an interestindication value exceeding a specified threshold value be returnedresponsive to the query. Further, the query may include further filtercriteria such as status criteria (e.g., only active items), categorycriteria (e.g., only return sales listings within a particular productor service category), website criteria (e.g., only return sales listingspublished via a country specific website operated by the publicationand/or sales system), price criteria (e.g., only return sales listingsfor which the current price is below a predetermined value), or any oneof a number of other criteria.

At block 138, the publication and/or sales system conducts a search ofinformation items by applying the information indication criteria to thestored interest indication values, and also by applying further criteriato further criteria values and information.

At block 140, information items that satisfy the search request areidentified, and included in a search result set that is then published,via the publication and/or sales system, at block 142.

The method then ends at block 150.

As noted above, the interest that is registered by the publicationand/or sales system in a particular information item may be registered,in one embodiment, responsive to a specific and affirmative indicationby the user of interest in the information item. In the example wherethe information item is a sales listing, published by a commerce site orelectronic marketplace, this interest indication may be received by theuser invoking a monitoring or flagging function with respect to the salelisting. The monitoring function, performed by the publication and/orsales system on behalf of the user, may present information regardingmonitored sales listing in a customized webpage (e.g., a portal webpagethat is customized for the particular user).

Further, the monitoring function may include providing alerts to theuser regarding activity (e.g., transaction activity) pertaining to thesale listings. For example, where the sale listing utilizes an auctionprice setting process, the monitoring function may provide acommunication (e.g., an email or other electronic notification) to theuser regarding bidding activity that has caused the price associatedwith a sale listing to increase. Further, where information presented inthe sale listing includes a fixed-priced item, and a seller, subsequentto publishing as the initial sale listing, reduces a fixed asking price,the monitoring function may also communicate this type of activitypertaining to the sales listing to the user.

Turning specifically to an exemplary embodiment in which the publicationand/or sales system is an electronic marketplace, the above describedtechnologies may serve to assist in establishing the relevance, orinterest levels, across dynamic and electronic marketplace.Specifically, the above described system may rank information items(e.g., sales listings) based on the number of “watches” or monitors orflags that are established with respect to an information item. In oneembodiment, the ability to initiate a monitoring function, or register aspecific interest indication, with respect to an information item may belimited to users that are registered with the publication and/or salessystem. In this way, the system may provide a “one-member, one-vote”function.

Accordingly, an embodiment of the present invention proposes makingvisible to other users, interest that users in aggregate have expressed,indicated or registered with respect to a particular information item.This aggregation and presentation of interest indications mayfurthermore be generalized to various methods of ranking, and otherwiseindicating relative relevancies. Further, by maintaining a count, orother measure, of registered interest indications with respect toinformation items, searching capabilities that are provided by thepublication and/or sales system may be enhanced.

According to one exemplary embodiment, there is provided a system and amethod to generate a list (e.g., a top 10) of most monitored (e.g.,“watched”) items per category per site to provide a dynamic overview ofconsumer interest levels within an electronic marketplace, to exposedemand and encourage similar purchases by buyers, to expose demand andencourage new supply from sellers, etc. The list of watched items may begenerated at least on a daily basis, and may be a generated as close toreal time as possible.

The following are exemplary features for the Most Watched Items.

Most Watched Items Batch Overview

Users can, in one embodiment, add an item to a list of monitored salelistings (e.g., to their “watch list” maintained at an electronicmarketplace). The Most watched items may be those active, “galleryfeatured” (or otherwise announced listings for) items that have thehighest watch count (e.g., the most number of users are watching them).In other embodiments, the “most watched” items may be those for whichthe respective sale of listing has otherwise been enhanced.

The items for the Most Watched Items may be filtered as follows:

If there is a filter (e.g., a category filter, price filter, statusfilter etc), items will be filtered accordingly.

In a further embodiment, only listings that have the gallery featurewill be included.

In yet a further embodiment, only items that are still currently activewill be included.

Exemplary Functional Specification

FIG. 6 is a flow chart illustrating a method 170, according to anexemplary embodiment of the present invention, to create a datastructure of sales listings in which users have expressed or registeredin interest.

In one embodiment, a MostWatchedItemsBatch job runs once a day. Thebatch job queries the SELLER_ITEM table and retrieves the watched itemsranked within top 10 based on the watch count.

An exemplary SQL query is:

select * from (a SELECT ITEM_ID , LEAF_CAT , PARENT_CAT, META_CAT,site_id , watch_count, rank( ) over (partition by leaf_cat , site_idorder by watch_count desc ) as dr FROM CASH_USER.SELLER_ITEM_CACHE_IOT_XWHERE WATCH_COUNT > 0 and end_time > sysdate ) where dr <= n

The batch job forms a Category tree per site (e.g., where an electronicmarketplace contains many websites) and fills in the top 10 watcheditems for each leaf and each meta category. It may query all the IOTsand merge the data into the category tree such that the Category treewill finally have top 20 watched items per category per site.

While adding the data into the category tree, the batch job may check ifthe item has gallery enabled by going against search backend. ??

Once the Category tree is filled with all the relevant data, the outputmay be written to XML files per site per category. This may be done by apool of threads.

Exemplary Batch job functionality

FIG. 7 is a high level flow chart illustrating a method 180, accordingto exemplary embodiment of the present invention, for creating acategory tree for the top n most watched items.

The exemplary method 180 includes the following operations:

-   -   1. Query the SELLER_ITEM (e.g., cached) tables fetching the        items ranked top n most ranked watched (monitored/flagged) items        per category per site. ‘n’ is configurable and is set to 10 by        default. The query may be done by calling a        “SellerSale.findMostWatchedActiveItems” method call. This query        may return a List object containing “SellerSaleCache”objects.    -   2. Create a hashmap per site encountered in the resultset if one        doesn't exist already.    -   3. Aggregate the list of most ranked watched items per category        and store it as a List object in a HashMap with category id as        the key.    -   4. For each item that potentially goes to the most watched list,        query the backend node to check if the item has gallery enabled.    -   5. If there are more rows in the resultset for the same        category/site, calculate the most watched 20 items and merge to        this list.    -   6. After processing all the leaf categories obtained from the        queries, browse the Category tree upwards using the CategoryBO.        Merge the top 20 items from all the children categories. Fill in        the list for all parent categories browsing upwards.    -   7. A MostWatchedltemsVO returns a XML model for the most watched        items for the given category and given site. This looks up the        hashmaps created while parsing the resultset.    -   8. A thread from a pool of threads may then pick up a category        from the list of all categories and writes out a serialized        version of the XML Model to a file named “<categoryId>.xml” in        directory “site_<siteId>”.

Once the batch is done, the scheduling chain may calls the script tosummarize the run results and email it to an alias. The scheduling chainmay be setup to run the batch every 24 hours. The scheduling chainshould, in one embodiment, not automatically attempt to restart thebatch if it failed. Instead the next scheduled run should be started asin a normal situation.

In one embodiment, the above-described operations may be performed as anentire back-end project, and no user interface (UI) and no user-visiblechanges may be presented on a website operated by an electronicmarketplace.

Exemplary XML Model

As noted above, in one embodiment, the batch job composes XML as theoutput per site id and per category.

Below is a sample XML document that specifies exemplary tags that may beused.

<?xml version=”1.0” encoding=”ISO-8859-1”?> < web site ><mostWatchedItems> <Item id=″5712669397″ rank=”1”/> ......... <Itemid=″4432146754″ rank=”20”/> </mostWatchedItems> </web site >One file per category per site may be created.

FIG. 8 shows a diagrammatic representation of machine in the exemplaryform of a computer system 300 within which a set of instructions, forcausing the machine to perform any one or more of the methodologiesdiscussed herein, may be executed. In alternative embodiments, themachine operates as a standalone device or may be connected (e.g.,networked) to other machines. In a networked deployment, the machine mayoperate in the capacity of a server or a client machine in server-clientnetwork environment, or as a peer machine in a peer-to-peer (ordistributed) network environment. The machine may be a server computer,a client computer, a personal computer (PC), a tablet PC, a set-top box(STB), a Personal Digital Assistant (PDA), a cellular telephone, a webappliance, a network router, switch or bridge, or any machine capable ofexecuting a set of instructions (sequential or otherwise) that specifyactions to be taken by that machine. Further, while only a singlemachine is illustrated, the term “machine” shall also be taken toinclude any collection of machines that individually or jointly executea set (or multiple sets) of instructions to perform any one or more ofthe methodologies discussed herein.

The exemplary computer system 300 includes a processor 302 (e.g., acentral processing unit (CPU) a graphics processing unit (GPU) or both),a main memory 304 and a static memory 306, which communicate with eachother via a bus 308. The computer system 300 may further include a videodisplay unit 310 (e.g., a liquid crystal display (LCD) or a cathode raytube (CRT)). The computer system 300 also includes an alphanumeric inputdevice 312 (e.g., a keyboard), a cursor control device 314 (e.g., amouse), a disk drive unit 316, a signal generation device 318 (e.g., aspeaker) and a network interface device 320.

The disk drive unit 316 includes a machine-readable medium 322 on whichis stored one or more sets of instructions (e.g., software 324)embodying any one or more of the methodologies or functions describedherein. The software 324 may also reside, completely or at leastpartially, within the main memory 304 and/or within the processor 302during execution thereof by the computer system 300, the main memory 304and the processor 302 also constituting machine-readable media. Thesoftware 324 may further be transmitted or received over a network 326via the network interface device 320.

While the machine-readable medium 392 is shown in an exemplaryembodiment to be a single medium, the term “machine-readable medium”should be taken to include a single medium or multiple media (e.g., acentralized or distributed database, and/or associated caches andservers) that store or embodies the one or more sets of instructions.The term “machine-readable medium” shall also be taken to include anymedium that is capable of storing, encoding or carrying a set ofinstructions for execution by the machine and that cause the machine toperform any one or more of the methodologies of the present invention.The term “machine-readable medium” shall accordingly be taken toinclude, but not be limited to, solid-state memories, optical andmagnetic media, and carrier wave signals.

Thus, a method and system to generate an aggregate indication for aninformation item have been described. Although the present invention hasbeen described with reference to specific exemplary embodiments, it willbe evident that various modifications and changes may be made to theseembodiments without departing from the broader spirit and scope of theinvention. Accordingly, the specification and drawings are to beregarded in an illustrative rather than a restrictive sense.

1. A computer system to process listing data, the system including: adatabase storing a plurality of listings published over a network; and aprocessor-implemented ranking module, of the computer system, to:determine a number of users from a plurality of users of the computersystem that are monitoring at least one listing, and generate a rankingfor the at least one listing based on the number of users monitoring theat least one listing.
 2. The computer system of claim 1, furtherincluding: a processor-implemented monitor component, of the computersystem, to monitor the plurality of listings on behalf of the pluralityof users; and wherein the processor-implemented ranking module is todetermine a number of users monitoring each listing of the plurality oflistings and to rank the plurality of listings based on the number ofusers monitoring each of the plurality of listings.
 3. The computersystem of claim 1, which includes at least one web server to publish theplurality of listings via the Internet to the plurality of users.
 4. Thecomputer system of claim 1, wherein monitoring criteria are receivedrelating to an extent to which the plurality of listings are monitoredby the plurality of users, and the computer system is to conduct asearch of the plurality of listings using the monitoring criteria.
 5. Acomputer system to process published listings, the system including:means for determining a number of users flagging a listing to monitorsubsequent activity; and means for generating a ranking for the listingbased on the number of users flagging the listing to monitor subsequentactivity, wherein each said means are processor-implemented componentsof the computer system.
 6. A computer-implemented method to establish aranking for published data, the method including: determining a numberof registrations of user interest in an instance of published data; andgenerating, by a computer, a ranking for the instance of published databased on the number of registrations of user interest in the instance ofpublished data.
 7. The method of claim 6, which includes registeringuser interest in the instance of published data by creating a datarecord associating a user with the instance of published data in amonitoring capacity.
 8. The method of claim 7, which includes enablingthe user to activate a monitoring process to monitor activity pertainingto the instance of published data on behalf of the user.
 9. The methodof claim 8, wherein the enabling of the user to activate the monitoringprocess includes enabling the user to specify a type of transactionactivity to be monitored on behalf of the user.
 10. The method of claim9, which includes actively monitoring activity pertaining to theinstance of published data, on behalf of the user.
 11. The method ofclaim 6, which includes publishing the ranking of the instance ofpublished data.
 12. The method of claim 6, which includes: monitoring aplurality of instances of published data on behalf of a plurality ofusers; determining a number of users monitoring each of the plurality ofinstances of published data; and ranking the plurality of instances ofpublished data based on the number of users monitoring each of theplurality of instances of published data.
 13. The method of claim 12,which includes publishing a list comprising a subset of the plurality ofinstances of published data monitored by more than a predeterminednumber of users.
 14. The method of claim 12, which includes receivingmonitoring criteria relating to an extent to which the plurality ofinstances of published data are monitored by the plurality of users, andconducting a search of the plurality of instances of published datausing the monitoring criteria.
 15. The method of claim 14, whichincludes receiving filter criteria, and conducting the search of theplurality of instances of published data using the filter criteria incombination with the monitoring criteria.
 16. The method of claim 15,wherein the further criteria includes any one of a group of filtercriteria including an instance of published data category, an instanceof published data price, an instance of published data attribute and aninstance of published data enhancement criteria.
 17. A machine-readablemedium embodying instructions which, when executed by a machine, causethe machine to execute a method to establish a ranking for an instanceof published data of a plurality of instances of published datapublished over a network, the method comprising: determining a number ofusers who have registered interest in an instance of published data; andgenerating a ranking for the instance of published data based on thedetermined number of users.